{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 1、",
   "id": "dd52354c66675007"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T11:21:53.234266Z",
     "start_time": "2025-01-07T11:21:53.228812Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import random\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from matplotlib import font_manager\n",
    "import time"
   ],
   "id": "initial_id",
   "outputs": [],
   "execution_count": 61
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 折线图",
   "id": "95b04217eb077a7a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T13:30:37.969080Z",
     "start_time": "2025-01-06T13:30:37.763822Z"
    }
   },
   "cell_type": "code",
   "source": [
    "x=range(2,26,2)\n",
    "y=[random.randint(15,30) for i in x]\n",
    "plt.plot(x,y,color='green',alpha=0.5,linestyle='--',marker='*')\n",
    "my_font=font_manager.FontProperties(fname=\"C:\\\\Windows\\\\Fonts\\\\STXINGKA.TTF\")\n",
    "x_lable=[f'{i}'for i in x]\n",
    "plt.xticks(x,x_lable)\n",
    "plt.xlabel('时间',fontproperties=my_font)\n",
    "y_lable=['{}`C'.format(i)for i in range(min(y),max(y)+1)]\n",
    "plt.yticks(range(min(y),max(y)+1),y_lable)\n",
    "plt.ylabel('次数',fontproperties=my_font)\n",
    "plt.savefig('ti.png')\n",
    "plt.savefig('ti.svg')\n",
    "plt.show()"
   ],
   "id": "5b833eb7f1fa04e4",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 45
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T13:30:30.995948Z",
     "start_time": "2025-01-06T13:30:30.870564Z"
    }
   },
   "cell_type": "code",
   "source": [
    "y1=[1,0,1,1,2,3,4,4,6,2,4,1,3,6,3,2,2,3,4,5]\n",
    "y2=[1,2,5,3,4,5,3,2,6,3,2,1,2,0,1,2,3,5,2,1]\n",
    "x=range(10,30)\n",
    "plt.plot(x,y1,color=\"green\",label='自己')\n",
    "plt.plot(x,y2,color=\"red\",label='同事')\n",
    "x_lable=['{}年'.format(i)for i in x]\n",
    "my_font=font_manager.FontProperties(fname=\"C:\\\\Windows\\\\Fonts\\\\STXINGKA.TTF\")\n",
    "plt.xticks(x,x_lable,fontproperties=my_font)\n",
    "plt.grid(alpha=0.4)\n",
    "plt.legend(prop=my_font,loc='upper right')\n",
    "plt.show()"
   ],
   "id": "6c767dfd8d8c8d8a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 44
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T14:01:42.403729Z",
     "start_time": "2025-01-06T14:01:42.204623Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "\n",
    "x  =  np.arange(1,  100) #划分子图\n",
    "fig,axes=plt.subplots(2,2)\n",
    "ax1=axes[0,0]\n",
    "ax2=axes[0,1] \n",
    "ax3=axes[1,0] \n",
    "ax4=axes[1,1]\n",
    "\n",
    "#fig=plt.figure(figsize=(20,10),dpi=80) \n",
    "ax1.plot(x, x)#作图1  \n",
    "ax2.plot(x, -x)# 作 图 2 \n",
    "ax3.plot(x, x**2)#作图3\n",
    "ax3.grid(color='r', linestyle='--', linewidth=1,alpha=0.3) \n",
    "ax4.plot(x, np.log(x)) #作图4\n",
    "plt.show()"
   ],
   "id": "283cddc9ffe5f288",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 49
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 绘制散点图",
   "id": "5a88b35131096e1a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T14:17:07.492227Z",
     "start_time": "2025-01-06T14:17:07.372694Z"
    }
   },
   "cell_type": "code",
   "source": [
    "y = [11, 17, 16, 11, 12, 11, 12, 6, 6, 7, 8, 9, 12, 15, 14, 17, 18, 21, 16, 17, 20, 14, 15, 15, 15, 19, 21, 22, 22, 22,\n",
    "     23]\n",
    "x = range( 1, 32 )\n",
    "\n",
    "# 设置图形大小\n",
    "plt.figure( figsize=(20, 8), dpi=80 )\n",
    "# 使用scatter绘制散点图\n",
    "plt.scatter( x, y, label='3月份' )\n",
    "# 调整x轴的刻度\n",
    "my_font = font_manager.FontProperties( fname=\"C:\\\\Windows\\\\Fonts\\\\STXINGKA.TTF\", size=10 )\n",
    "\n",
    "x_labels = ['3月{}日'.format( i ) for i in x]\n",
    "\n",
    "plt.xticks( x[::3], x_labels[::3], fontproperties=my_font, rotation=45 )\n",
    "plt.xlabel( ' 日 期 ', fontproperties=my_font )\n",
    "plt.ylabel( '温度', fontproperties=my_font )\n",
    "plt.grid( alpha=0.4 )\n",
    "# 图 例\n",
    "plt.legend( prop=my_font )#自定义字体\n",
    "plt.show()"
   ],
   "id": "3b5f449a40869e41",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x640 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 52
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 条形图",
   "id": "66f2b910e65a7afa"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T14:28:19.721237Z",
     "start_time": "2025-01-06T14:28:19.616641Z"
    }
   },
   "cell_type": "code",
   "source": [
    "my_font =  font_manager.FontProperties(fname=\"C:\\\\Windows\\\\Fonts\\\\STXINGKA.TTF\",size=16)\n",
    "a = ['流浪地球','疯狂的外星人','飞驰人生','大黄蜂','熊出没·原始时代','新喜剧之王']\n",
    "b = [38.13,19.85,14.89,11.36,6.47,5.93]\n",
    "\n",
    "plt.figure(figsize=(20,8),dpi=80) # 设置画布大小\n",
    "\n",
    "# 绘制条形图的方法\n",
    "'''\n",
    "width=0.3  条形的宽度\n",
    "'''\n",
    "rects = plt.bar(range(len(a)),b,width=0.3,color='r') # 绘制条形图\n",
    "plt.xticks(range(len(a)),a,fontproperties=my_font,rotation=45) # 设置x轴的标签\n",
    "for rect in rects:\n",
    "    height = rect.get_height() # 获取条形的高度\n",
    "    plt.text(rect.get_x()+rect.get_width()/2,height+0.5,'%.2f'%height,ha='center',va='bottom',fontproperties=my_font) # 设置条形的数值 1.rect.get_x()获取x坐标 2.rect.get_width()/2宽度除2使票房数据位于中间 3.height+0.5 数据位于柱子上方 4.ha='center'ha='center'数字与x坐标中心，底部对齐\n",
    "plt.show()"
   ],
   "id": "56a9a109e2111cf8",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x640 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 54
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 直方图",
   "id": "96528b6ace7e17bd"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T14:29:10.623595Z",
     "start_time": "2025-01-06T14:29:10.616059Z"
    }
   },
   "cell_type": "code",
   "source": [
    "time = [131,   98,    125,   131,   124,   139,   131, 117, 128, 108, 135, 138, 131, 102, 107, 114,\n",
    "119,   128,   121,   142,   127,   130,   124, 101, 110, 116, 117, 110, 128, 128, 115,   99,\n",
    "136,   126,   134,   95,    138,   117,   111,78, 132, 124, 113, 150, 110, 117,  86,    95, 144,\n",
    "105, 126, 130,126, 130, 126, 116, 123, 106, 112, 138, 123, 86, 101,   99, 136,123,\n",
    "117,   119,   105,   137, 123, 128, 125, 104, 109, 134, 125, 127,105, 120,  107,   129, 116,\n",
    "108,   132,   103,   136, 118, 102, 120, 114,105, 115, 132, 145, 119, 121,  112,   139, 125,\n",
    "138,   109,   132,   134,156, 106, 117, 127, 144, 139, 139, 119, 140,   83,    110,   102,123,\n",
    "107,   143,   115,   136, 118, 139, 123, 112, 118, 125, 109, 119, 133,112,  114,   122, 109,\n",
    "106,   123,   116,   131,   127, 115, 118, 112, 135,115,   146,   137,   116,   103,   144,   83,    123,\n",
    "111,   110,   111,   100,   154,136, 100, 118, 119, 133,   134,   106,   129,   126,   110,   111,   109,\n",
    "141,120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126,114, 140, 103,\n",
    "130,   141, 117, 106, 114, 121, 114, 133, 137,    92,121,    112,   146,   97,    137, 105,  98,\n",
    "117,   112,   81,    97, 139, 113,134, 106, 144, 110, 137,  137,   111,   104,   117, 100, 111,\n",
    "101,   110,105, 129, 137, 112, 120, 113, 133, 112,    83,    94,    146,   133,   101,131, 116,\n",
    "111,   84, 137, 115, 122, 106, 144, 109, 123, 116, 111,111, 133, 150]\n"
   ],
   "id": "d9254bdc88fb0817",
   "outputs": [],
   "execution_count": 55
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T14:29:24.293650Z",
     "start_time": "2025-01-06T14:29:23.963Z"
    }
   },
   "cell_type": "code",
   "source": [
    "plt.figure(figsize=(20, 8), dpi=100) # 3）绘制直方图\n",
    "print(max(time),min(time))\n",
    "# 设置组距\n",
    "distance = 2\n",
    "# 计算组数\n",
    "group_num = int((max(time) - min(time)) / distance) # 绘制直方图\n",
    "plt.hist(time, bins=group_num)\n",
    "\n",
    "# 修改x轴刻度显示\n",
    "plt.xticks(range(min(time), max(time))[::2])\n",
    "plt.yticks(range(0, 20, 1))\n",
    "\n",
    "# 添加网格显示\n",
    "plt.grid(linestyle=\"--\", alpha=0.5)\n",
    "\n",
    "#添 加 x,  y 轴 描 述 信 息\n",
    "plt.xlabel(\"电影时长大小\",fontproperties=my_font)\n",
    "plt.ylabel(\"电影的数据量\",fontproperties=my_font)\n",
    "# 4）显示图像\n",
    "plt.show()"
   ],
   "id": "bda9a130a9c4c480",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "156 78\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 56
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 饼图",
   "id": "ee8141f683aa5b52"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-06T14:32:16.666130Z",
     "start_time": "2025-01-06T14:32:16.519462Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import matplotlib\n",
    "label_list = [\"第一部分\", \"第二部分\", \"第三部分\"]  # 各部分标签\n",
    "size = [55, 35, 10]    # 各部分大小\n",
    "color = [\"red\", \"green\", \"blue\"]   # 各部分颜色\n",
    "explode = [0, 0.05, 0] # 各部分突出值\n",
    "# 绘制饼图\n",
    "plt.figure(figsize=(20, 8), dpi=100)\n",
    "# plt.pie(size, labels=label_list, colors=color, explode=explode, autopct='%1.1f%%', shadow=True, startangle=140)\n",
    "matplotlib.rcParams['font.sans-serif']=['SimHei']\n",
    "patches, l_text, p_text = plt.pie(size,explode=explode, colors=color, labels=label_list,\n",
    "                                  labeldistance=1.1, autopct=\"%1.1f%%\", shadow=True, startangle=90, pctdistance=0.5)\n",
    "plt.axis(\"equal\")  # 设置横轴和纵轴大小相等，这样饼才是圆的\n",
    "plt.legend()\n",
    "plt.show()"
   ],
   "id": "3c979c4da2a7c28d",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 57
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 2、",
   "id": "5099db39599f044d"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T11:19:07.407497Z",
     "start_time": "2025-01-07T11:19:07.393492Z"
    }
   },
   "cell_type": "code",
   "source": [
    "#列表转ndarray\n",
    "list1=[1,2,3,4]\n",
    "print(list1)\n",
    "print(type(list1))\n",
    "one=np.array(list1)\n",
    "print(type(one))\n",
    "print(one)"
   ],
   "id": "bd774ed96cc1482b",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4]\n",
      "<class 'list'>\n",
      "<class 'numpy.ndarray'>\n",
      "[1 2 3 4]\n"
     ]
    }
   ],
   "execution_count": 60
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T11:33:29.095009Z",
     "start_time": "2025-01-07T11:33:28.915615Z"
    }
   },
   "cell_type": "code",
   "source": [
    "a=[]\n",
    "for i in range(1000000):\n",
    "    a.append(random.random())\n",
    "print('随机完毕')\n",
    "t1=time.time()\n",
    "sum1=sum(a)\n",
    "t2=time.time()\n",
    "b=np.array(a)\n",
    "print('转换完毕')\n",
    "t3=time.time()\n",
    "sum2=np.sum(b)\n",
    "t4=time.time()\n",
    "print(t2 - t1,t4 - t3)"
   ],
   "id": "41e5153ccdc3fbe7",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "随机完毕\n",
      "转换完毕\n",
      "0.00598454475402832 0.0019483566284179688\n"
     ]
    }
   ],
   "execution_count": 64
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 3、",
   "id": "ed0550fb3a434ca6"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 二维",
   "id": "3b6232fa410c9363"
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1, 2], [3, 4], [5, 6]]\n",
      "<class 'list'>\n",
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n",
      "<class 'numpy.ndarray'>\n"
     ]
    }
   ],
   "execution_count": 68,
   "source": [
    "list2=[[1,2],[3,4],[5,6]]\n",
    "two=np.array(list2)\n",
    "print(list2)\n",
    "print(type(list2))\n",
    "print(two)\n",
    "print(type(two))"
   ],
   "id": "d0c2a80c7d6657c8"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 属性",
   "id": "e9684a3af689d6a4"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T12:37:50.922184Z",
     "start_time": "2025-01-07T12:37:50.917985Z"
    }
   },
   "cell_type": "code",
   "source": [
    "list2=[[1,2],[3,4],[5,6]]\n",
    "two=np.array(list2)\n",
    "print(two.ndim)\n",
    "print(two.shape)\n",
    "print(two.size)\n",
    "print(two.dtype)"
   ],
   "id": "64adb5fc13ef4fee",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "(3, 2)\n",
      "6\n",
      "int64\n"
     ]
    }
   ],
   "execution_count": 70
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 数组形状",
   "id": "9119df305aec4b8"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T12:41:37.487036Z",
     "start_time": "2025-01-07T12:41:37.482177Z"
    }
   },
   "cell_type": "code",
   "source": [
    "four=np.array([[1,2,3],[4,5,6]])\n",
    "print(four)\n",
    "four1=four\n",
    "print(id(four))\n",
    "four.shape=(3,2)\n",
    "print(id(four))\n",
    "print(id(four1))\n",
    "print(four)"
   ],
   "id": "bac05eea74e5c569",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n",
      "2614854916432\n",
      "2614854916432\n",
      "2614854916432\n",
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n"
     ]
    }
   ],
   "execution_count": 71
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T13:02:54.225178Z",
     "start_time": "2025-01-07T13:02:54.218956Z"
    }
   },
   "cell_type": "code",
   "source": [
    "four=four.reshape(3,2)\n",
    "four1=four\n",
    "print(four)\n",
    "print(id(four))\n",
    "five=four.reshape((6),order=\"c\")\n",
    "six=four.flatten()\n",
    "print(five)\n",
    "print(six)\n",
    "print(five.reshape(3,2))"
   ],
   "id": "5b389fedcde2e836",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n",
      "2614854820624\n",
      "[1 2 3 4 5 6]\n",
      "[1 2 3 4 5 6]\n",
      "[[1 2]\n",
      " [3 4]\n",
      " [5 6]]\n"
     ]
    }
   ],
   "execution_count": 73
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T13:18:28.229146Z",
     "start_time": "2025-01-07T13:18:28.217153Z"
    }
   },
   "cell_type": "code",
   "source": [
    "seven=five.reshape(3,2)\n",
    "seven"
   ],
   "id": "a9aa2b0bd4b85510",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2],\n",
       "       [3, 4],\n",
       "       [5, 6]])"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 74
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T13:34:33.383784Z",
     "start_time": "2025-01-07T13:34:33.377629Z"
    }
   },
   "cell_type": "code",
   "source": [
    "t=np.arange(24)\n",
    "print(t)\n",
    "print(t.shape)\n",
    "print(t.ndim)\n",
    "t1=t.reshape((4,6))#二维\n",
    "print(t1)\n",
    "print(t1.shape)\n",
    "print('-'*50)\n",
    "t2=t.reshape((2,3,4))#e三维\n",
    "print(t2)\n",
    "print(t2.shape)\n",
    "print('-'*50)\n",
    "t3=t.reshape((2,2,2,3))#四维\n",
    "print(t3)\n",
    "print(t3.shape)"
   ],
   "id": "fafa05a7711e7e22",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
      "(24,)\n",
      "1\n",
      "[[ 0  1  2  3  4  5]\n",
      " [ 6  7  8  9 10 11]\n",
      " [12 13 14 15 16 17]\n",
      " [18 19 20 21 22 23]]\n",
      "(4, 6)\n",
      "--------------------------------------------------\n",
      "[[[ 0  1  2  3]\n",
      "  [ 4  5  6  7]\n",
      "  [ 8  9 10 11]]\n",
      "\n",
      " [[12 13 14 15]\n",
      "  [16 17 18 19]\n",
      "  [20 21 22 23]]]\n",
      "(2, 3, 4)\n",
      "--------------------------------------------------\n",
      "[[[[ 0  1  2]\n",
      "   [ 3  4  5]]\n",
      "\n",
      "  [[ 6  7  8]\n",
      "   [ 9 10 11]]]\n",
      "\n",
      "\n",
      " [[[12 13 14]\n",
      "   [15 16 17]]\n",
      "\n",
      "  [[18 19 20]\n",
      "   [21 22 23]]]]\n",
      "(2, 2, 2, 3)\n"
     ]
    }
   ],
   "execution_count": 77
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# Numpy的数据类型",
   "id": "92db670eb5af0d0a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T13:38:59.028352Z",
     "start_time": "2025-01-07T13:38:59.024357Z"
    }
   },
   "cell_type": "code",
   "source": [
    "f=np.array([1,2,3,4,5],dtype=np.int16)\n",
    "print(f.itemsize)\n",
    "print(f.dtype)"
   ],
   "id": "3dc47cb18fca1214",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "int16\n"
     ]
    }
   ],
   "execution_count": 78
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T13:49:52.024170Z",
     "start_time": "2025-01-07T13:49:52.018733Z"
    }
   },
   "cell_type": "code",
   "source": [
    "print(round(random.random(),2))\n",
    "arr=np.array([random.random()for i in range(10)])\n",
    "print(arr)\n",
    "print(arr.itemsize)\n",
    "print(arr.dtype)\n",
    "print(np.round(arr,2))"
   ],
   "id": "22795b66b48cd5b1",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.92\n",
      "[0.46433469 0.1315845  0.14935609 0.49486659 0.598064   0.06478697\n",
      " 0.29518549 0.09767257 0.9726611  0.43319044]\n",
      "8\n",
      "float64\n",
      "[0.46 0.13 0.15 0.49 0.6  0.06 0.3  0.1  0.97 0.43]\n"
     ]
    }
   ],
   "execution_count": 79
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 数组与数的运算",
   "id": "b080dfa94aac0fd6"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T13:54:13.158031Z",
     "start_time": "2025-01-07T13:54:13.151196Z"
    }
   },
   "cell_type": "code",
   "source": [
    "t1=np.arange(24).reshape(6,4)\n",
    "print(t1)\n",
    "t2=t1.tolist()\n",
    "print(t1+2)\n",
    "print(t1*2)\n",
    "print(t1/2)"
   ],
   "id": "edc09482652133e5",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0  1  2  3]\n",
      " [ 4  5  6  7]\n",
      " [ 8  9 10 11]\n",
      " [12 13 14 15]\n",
      " [16 17 18 19]\n",
      " [20 21 22 23]]\n",
      "[[ 2  3  4  5]\n",
      " [ 6  7  8  9]\n",
      " [10 11 12 13]\n",
      " [14 15 16 17]\n",
      " [18 19 20 21]\n",
      " [22 23 24 25]]\n",
      "[[ 0  2  4  6]\n",
      " [ 8 10 12 14]\n",
      " [16 18 20 22]\n",
      " [24 26 28 30]\n",
      " [32 34 36 38]\n",
      " [40 42 44 46]]\n",
      "[[ 0.   0.5  1.   1.5]\n",
      " [ 2.   2.5  3.   3.5]\n",
      " [ 4.   4.5  5.   5.5]\n",
      " [ 6.   6.5  7.   7.5]\n",
      " [ 8.   8.5  9.   9.5]\n",
      " [10.  10.5 11.  11.5]]\n"
     ]
    }
   ],
   "execution_count": 80
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T13:56:58.686787Z",
     "start_time": "2025-01-07T13:56:58.680144Z"
    }
   },
   "cell_type": "code",
   "source": [
    "t1=np.arange(24).reshape(4,6)\n",
    "t2=np.arange(6).reshape(1,6)\n",
    "print(t2.shape)\n",
    "print(t1)\n",
    "print(t2)\n",
    "t1-t2"
   ],
   "id": "4a71b4571455e093",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 6)\n",
      "[[ 0  1  2  3  4  5]\n",
      " [ 6  7  8  9 10 11]\n",
      " [12 13 14 15 16 17]\n",
      " [18 19 20 21 22 23]]\n",
      "[[0 1 2 3 4 5]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 0,  0,  0,  0,  0,  0],\n",
       "       [ 6,  6,  6,  6,  6,  6],\n",
       "       [12, 12, 12, 12, 12, 12],\n",
       "       [18, 18, 18, 18, 18, 18]])"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 81
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 轴",
   "id": "5b763cf87607e7d0"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:04:12.200024Z",
     "start_time": "2025-01-07T14:04:12.176446Z"
    }
   },
   "cell_type": "code",
   "source": [
    "a=np.array([[1,2,3],[4,5,6]])\n",
    "print(a)\n",
    "print(np.sum(a,axis=0))#轴0求和\n",
    "print(np.sum(a,axis=1))#轴1求和\n",
    "print(np.sum(a))"
   ],
   "id": "3443bddcf72994b4",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 2 3]\n",
      " [4 5 6]]\n",
      "[5 7 9]\n",
      "[ 6 15]\n",
      "21\n"
     ]
    }
   ],
   "execution_count": 82
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "# 5、\n",
    "## 索引和切片"
   ],
   "id": "bf00d3d85c18b564"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:09:33.445887Z",
     "start_time": "2025-01-07T14:09:33.441889Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "\n",
    "a = np.arange(10)\n",
    "# 冒号分隔切片参数 start:stop:step 来进行切片操作print(a[2:7:2])# 从索引 2 开始到索引 7 停止，间隔为 2\n",
    "\n",
    "# 如果只放置一个参数，如 [2]，将返回与该索引相对应的单个元素\n",
    "print(a[0], a)\n",
    "\n",
    "# 如果为 [2:]，表示从该索引开始以后的所有项都将被提取\n",
    "print(a[2:])\n",
    "\n",
    "print(a[2:8:2])  "
   ],
   "id": "ce770232e800de3d",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 [0 1 2 3 4 5 6 7 8 9]\n",
      "[2 3 4 5 6 7 8 9]\n",
      "[2 4 6]\n"
     ]
    }
   ],
   "execution_count": 83
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:09:46.365976Z",
     "start_time": "2025-01-07T14:09:46.360282Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "\n",
    "t1 = np.arange(24).reshape(4, 6)\n",
    "print(t1)\n",
    "print('*' * 20)\n",
    "print(t1[1])  # 取一行(一行代表是一条数据，索引也是从0开始的) print(t1[1,:]) # 取一行\n",
    "print('*' * 20)\n",
    "print(t1[1:])  # 取连续的多行\n",
    "print('*' * 20)\n",
    "print(t1[1:3, :])  # 取连续的多行\n",
    "print('*' * 20)\n",
    "print(t1[[0, 2, 3]])  #"
   ],
   "id": "e739c6dd162b22ca",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0  1  2  3  4  5]\n",
      " [ 6  7  8  9 10 11]\n",
      " [12 13 14 15 16 17]\n",
      " [18 19 20 21 22 23]]\n",
      "********************\n",
      "[ 6  7  8  9 10 11]\n",
      "********************\n",
      "[[ 6  7  8  9 10 11]\n",
      " [12 13 14 15 16 17]\n",
      " [18 19 20 21 22 23]]\n",
      "********************\n",
      "[[ 6  7  8  9 10 11]\n",
      " [12 13 14 15 16 17]]\n",
      "********************\n",
      "[[ 0  1  2  3  4  5]\n",
      " [12 13 14 15 16 17]\n",
      " [18 19 20 21 22 23]]\n"
     ]
    }
   ],
   "execution_count": 84
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:10:24.580397Z",
     "start_time": "2025-01-07T14:10:24.571685Z"
    }
   },
   "cell_type": "code",
   "source": [
    "print(t1[:, 1])  # 取一列\n",
    "print('*' * 20)\n",
    "print(t1[:, 1:])  # 连续的多列\n",
    "print('*' * 20)\n",
    "print(t1[:, [0, 2, 3]])  # 取不连续的多列\n",
    "print('*' * 20)\n",
    "print(t1[2, 3])  # # 取某一个值,三行四列  py是t1[2][3]\n",
    "print('*' * 20)\n",
    "print(t1[[0, 1, 1], [0, 1, 3]])  # 取多个不连续的值，[[行，行。。。],[列，列。。。]]\n",
    "\n",
    "t1[1:3, 1:4]  #取1-3行，1-4列"
   ],
   "id": "c6d840c2a48fe502",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1  7 13 19]\n",
      "********************\n",
      "[[ 1  2  3  4  5]\n",
      " [ 7  8  9 10 11]\n",
      " [13 14 15 16 17]\n",
      " [19 20 21 22 23]]\n",
      "********************\n",
      "[[ 0  2  3]\n",
      " [ 6  8  9]\n",
      " [12 14 15]\n",
      " [18 20 21]]\n",
      "********************\n",
      "15\n",
      "********************\n",
      "[0 7 9]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 7,  8,  9],\n",
       "       [13, 14, 15]])"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 85
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## 修改值",
   "id": "15dcd156b71610c9"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:11:56.986623Z",
     "start_time": "2025-01-07T14:11:56.978526Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "\n",
    "t = np.arange(24).reshape(4, 6)\n",
    "print(t)\n",
    "print(id(t))\n",
    "# # 修改某一行的值\n",
    "# t[1,:]=0\n",
    "#\n",
    "# # 修改某一列的值\n",
    "# t[:,1]=0\n",
    "#\n",
    "# # 修改连续多行\n",
    "# t[1:3,:]=0\n",
    "#\n",
    "# # 修改连续多列\n",
    "# t[:,1:4]=0\n",
    "#\n",
    "# # 修改多行多列，取第二行到第四行，第三列到第五列\n",
    "# t[1:3,2:5]=0\n",
    "#\n",
    "# # 修改多个不相邻的点\n",
    "# t[[0,1],[1,3]]=0\n",
    "\n",
    "# 可以根据条件修改，比如讲小于10的值改掉\n",
    "# t[t<10]=0\n",
    "\n",
    "# 使用逻辑判断\n",
    "# np.logical_and\t& # np.logical_or\t|\n",
    "# np.logical_not\t\t~\n",
    "# t[(t>2)&(t<6)]=0\t# 逻辑与，and\n",
    "# t[(t<2)|(t>6)]=0\t# 逻辑或，or\n",
    "# t[~(t>6)]=0\t# 逻辑非\n",
    "# print(t)\n",
    "t = t.clip(10, 18)\n",
    "print(id(t))\n",
    "t"
   ],
   "id": "5d16132133c633e8",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0  1  2  3  4  5]\n",
      " [ 6  7  8  9 10 11]\n",
      " [12 13 14 15 16 17]\n",
      " [18 19 20 21 22 23]]\n",
      "2614854814672\n",
      "2614946058416\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[10, 10, 10, 10, 10, 10],\n",
       "       [10, 10, 10, 10, 10, 11],\n",
       "       [12, 13, 14, 15, 16, 17],\n",
       "       [18, 18, 18, 18, 18, 18]])"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 87
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:12:15.843865Z",
     "start_time": "2025-01-07T14:12:15.838665Z"
    }
   },
   "cell_type": "code",
   "source": [
    "t = np.arange(24).reshape(4, 6)\n",
    "t < 10\n",
    "#t的值小于10为true，大于等于10为false"
   ],
   "id": "e99b09044ccc406e",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ True,  True,  True,  True,  True,  True],\n",
       "       [ True,  True,  True,  True, False, False],\n",
       "       [False, False, False, False, False, False],\n",
       "       [False, False, False, False, False, False]])"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 88
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:14:00.742200Z",
     "start_time": "2025-01-07T14:14:00.737638Z"
    }
   },
   "cell_type": "code",
   "source": [
    "a = 10\n",
    "b = 15\n",
    "c = a if a > b else b\n",
    "c\n",
    "#输出大数"
   ],
   "id": "44373ad14586e384",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 90
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:14:02.448434Z",
     "start_time": "2025-01-07T14:14:02.444333Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# # 拓 展\n",
    "# # 三目运算（ np.where(condition, x, y)满足条件(condition)，输出x，不满足输出y。)）\n",
    "score = np.array([[80, 88], [82, 81], [75, 81]])\n",
    "print(score)\n",
    "result = np.where(score < 80, True, False)  #类似于if else\n",
    "print(result)\n"
   ],
   "id": "506cdfbb9916842d",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[80 88]\n",
      " [82 81]\n",
      " [75 81]]\n",
      "[[False False]\n",
      " [False False]\n",
      " [ True False]]\n"
     ]
    }
   ],
   "execution_count": 91
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-07T14:14:35.496998Z",
     "start_time": "2025-01-07T14:14:35.492222Z"
    }
   },
   "cell_type": "code",
   "source": [
    "score[result] = 100\n",
    "score"
   ],
   "id": "d5327006bc19a5ed",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 80,  88],\n",
       "       [ 82,  81],\n",
       "       [100,  81]])"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 92
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "",
   "id": "9278dabfaf7f4b75"
  }
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